Joint decision-making of production and maintenance in mixed model assembly systems with delayed differentiation configurations
Weihong Guo and
Xi Gu
International Journal of Production Research, 2020, vol. 58, issue 13, 4071-4085
Abstract:
Mixed model assembly systems (MMASs) can simultaneously manufacture multiple product variants and are developed to satisfy customers’ increasing desire for products with a high variety. This paper investigates the joint decision-making of production and maintenance policies in MMASs with delayed differentiation configurations, where common operations are performed before differentiated processes. The problem is formulated as a Markov Decision Process (MDP) problem that minimises the average cost per unit time. Monte Carlo simulation is used to evaluate the system performance measures (e.g. volume mix ratio, product quality) under the optimal policy. Numerical examples are presented to illustrate the structure of the optimal policy and the impact of different factors on the system performance in an MMAS that produces two types of product variants. Techniques that can potentially solve the problem in large-sized MMASs are also discussed.
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2019.1641641 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:58:y:2020:i:13:p:4071-4085
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2019.1641641
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().